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Empirical Validation of Objective Functions in Feature Selection Based on Acceleration Motion Segmentation Data
المؤلفون المشاركون
Lim, Jong Gwan
Kim, Mi-hye
Lee, Sahngwoon
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-10-11
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Recent change in evaluation criteria from accuracy alone to trade-off with time delay has inspired multivariate energy-based approaches in motion segmentation using acceleration.
The essence of multivariate approaches lies in the construction of highly dimensional energy and requires feature subset selection in machine learning.
Due to fast process, filter methods are preferred; however, their poorer estimate is of the main concerns.
This paper aims at empirical validation of three objective functions for filter approaches, Fisher discriminant ratio, multiple correlation (MC), and mutual information (MI), through two subsequent experiments.
With respect to 63 possible subsets out of 6 variables for acceleration motion segmentation, three functions in addition to a theoretical measure are compared with two wrappers, k-nearest neighbor and Bayes classifiers in general statistics and strongly relevant variable identification by social network analysis.
Then four kinds of new proposed multivariate energy are compared with a conventional univariate approach in terms of accuracy and time delay.
Finally it appears that MC and MI are acceptable enough to match the estimate of two wrappers, and multivariate approaches are justified with our analytic procedures.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Lim, Jong Gwan& Kim, Mi-hye& Lee, Sahngwoon. 2015. Empirical Validation of Objective Functions in Feature Selection Based on Acceleration Motion Segmentation Data. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1073395
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Lim, Jong Gwan…[et al.]. Empirical Validation of Objective Functions in Feature Selection Based on Acceleration Motion Segmentation Data. Mathematical Problems in Engineering No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1073395
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Lim, Jong Gwan& Kim, Mi-hye& Lee, Sahngwoon. Empirical Validation of Objective Functions in Feature Selection Based on Acceleration Motion Segmentation Data. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1073395
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1073395
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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